Chaotic Characteristics of Workface Gas Emission Time-Series Data

Author:

Qiao Mei Ying1,Lan Jian Yi1

Affiliation:

1. Henan Polytechnic University

Abstract

The chaotic time series phase space reconstruction theory based in this paper. First, the appropriate embedding dimension and delay time are selected by minimum entropy rate. Followed the chaotic behavior are analyzed by the use of the Poincare section map and Power spectrum of time series from the qualitative point of view. Based on NLSR LLE the quantitative study of the chaotic time series characteristics indicators is proposed. Finally, the gas emission workface of Hebi 10th Mine Coal is studied. The several analytical results of the above methods show that: the gas emission time-series data of this workface has chaotic characteristics.

Publisher

Trans Tech Publications, Ltd.

Reference13 articles.

1. C. Zhuyun. Research of non-linear prediction and identification omen of coal and gas outburst by support vector machines [D], China University Mining and Technology, (2009).

2. C. Jian, Bai Jingyi , QIAN Jiansheng, Short-Term Forecasting Method of coalmine Gas Concentration Based on Chaotic Time Series[J], Journal of China University of Mining & Technology2008, 27(02): 231~235.

3. S. Shiliang, SONG Yi1, HE Liwen. Research on determ ination of chaotic characteristics of gas gush based on time series in excavation working face of coal mine[J]. Journal of China Coal Society. 2006, 31(6): 701~705.

4. F. Takens. Detecting strange attractors in turbulence. [J]. Dynamical Systems and Turbulence, 1981, 898: 366~381.

5. Q. Meiying, Ma Xiaoping, Lan Jianyi. Time Series Short Term Gas Prediction Based on Weighted LS-SVM [J]. Journal o f Mining & Safet y Engineering, 2011, 28 (2): 310~314.

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1. The dynamic analysis of a chaotic system;Advances in Mechanical Engineering;2017-03

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